Senior Staff Software Engineer

Palo Alto Networks

Confirmed live today High trust

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $153,700–$248,600 / yr
Posted: 7 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $193k

This role $201k

$128k $279k

below market most similar roles pay here above market

This role pays less than 55% of similar roles. Most pay $166,125–$219,425 — the blue band above. At the midpoint, this role pays about $201k versus about $193k for comparable roles.

Based on 240 similar postings.

Employer

About Palo Alto Networks

Palo Alto Networks is a global cybersecurity company offering network security, cloud security, and endpoint protection solutions.

Palo Alto Networks currently has 51 open roles on FindRole.

Listed pay typically runs $159,100–$257,400 across 47 roles with salary data.

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View all roles at Palo Alto Networks

At a glance

TL;DR · Senior Staff Software Engineer

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The Sr. Staff Software Engineer joins the Information Technology team as an AI-Native Cloud FinOps Engineer to build intelligent pipelines and autonomous optimization systems for cloud spend across AWS, Azure, and GCP. This role focuses on AI/ML compute infrastructure, specifically managing GPU clusters, model batching, and LLM pipelines. You will engineer closed-loop software systems to convert detected optimizations into automated savings and build infrastructure-as-code pipelines. Key responsibilities include training predictive machine learning models to analyze usage telemetry and designing internal AI agents to detect waste. Required technical skills include Python, ReAct, TypeScript/Node.js, LangChain, Terraform, and Pulumi. You will also utilize LLM APIs, vector databases, and FinOps APIs to solve the technical problem of multi-cloud financial efficiency and unit economics for high-cost AI workloads.

What does a Software Engineer earn in California?

Median $214500 from 1193 postings across 76 companies.

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Skills

Python TypeScript Node.js Terraform Pulumi AWS Azure GCP LangChain Kubernetes SQL BigQuery Snowflake CI/CD Vector Databases LLM APIs Machine Learning FinOps Kubecost OpenCost

What you'll do

Engineer autonomous systems using LangChain and ADK to inspect and optimize high-cost AI/ML workloads.
Programmatically manage GPU cluster provisioning, optimize model batching, and track per-token unit economics.
Write closed-loop software systems that automatically convert detected optimization opportunities into executed savings.
Build infrastructure-as-code pipelines using Terraform and Pulumi with real-time cost-compilation checks.
Train and deploy predictive machine learning models to analyze real-time usage telemetry and detect spend anomalies.
Build telemetry platforms to measure unit economics and lead the technical evolution of FinOps maturity.
Design internal AI agents to analyze infrastructure state, detect waste, and submit pre-validated Pull Requests.

What we're looking for

Minimum 8+ years of experience in Software Engineering, Cloud Engineering, SRE, or Cloud FinOps teams.
2+ years of hands-on experience building software tools or AI/ML integrations for cloud resource management.
Strong software engineering fundamentals in Python, ReAct, and TypeScript/Node.js.
Practical experience interfacing with LLM APIs, vector databases, and agentic frameworks.
Deep understanding of the architectural and financial cost drivers of AI/ML workloads.
Hands-on programmatic experience interacting with FinOps APIs across AWS, GCP, and Azure.
Mastery of IaC tools like Terraform and Pulumi, combined with CI/CD engine experience.
Proven track record of architecting and maintaining closed-loop automation tools in multi-cloud environments.
Must be local to Bay area to be onsite.
Experience with Kubernetes cost allocation using tools like Kubecost or OpenCost (preferred).
Proficiency with big-data querying tools like SQL, BigQuery, or Snowflake to process billing exports (preferred).
Ability to partner with AI/ML Engineers, Product Leaders, and FP&A to align infrastructure strategies with financial goals (preferred).
A software-first, agentic problem-solving mindset focused on writing self-healing systems (preferred).

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